> I think it can yield the highest success rate.
At what?
If you want to be an SRE for a data platform, sure, but this pretty thankless work:
- cleaning up dodgy data
- cleaning up behind low code data pipelines and other painful integration work with systems that suck and sometimes just don’t work (like PowerBI).
- cleaning up behind data scientists that create models in arcane and imaginative ways and expect you to “productionise” them.
- cleaning up behind brain dead scheduling systems that fail unexpectedly.
- constant churn with partners and cloud products for whatever the latest hotness is.
If you want to be solving actual problems with ML, this is a dead end.
It’s IT support for the people doing real work.
…so, it depends on your goals. Getting a job? Sure! Everyone wants a workhorse who they can dump all the annoying problematic on-call tasks to.
Learning ML, contributing to research, building models?
This isn’t a path that leads there.
At what?
If you want to be an SRE for a data platform, sure, but this pretty thankless work:
- cleaning up dodgy data
- cleaning up behind low code data pipelines and other painful integration work with systems that suck and sometimes just don’t work (like PowerBI).
- cleaning up behind data scientists that create models in arcane and imaginative ways and expect you to “productionise” them.
- cleaning up behind brain dead scheduling systems that fail unexpectedly.
- constant churn with partners and cloud products for whatever the latest hotness is.
If you want to be solving actual problems with ML, this is a dead end.
It’s IT support for the people doing real work.
…so, it depends on your goals. Getting a job? Sure! Everyone wants a workhorse who they can dump all the annoying problematic on-call tasks to.
Learning ML, contributing to research, building models?
This isn’t a path that leads there.